Abstract
The availability of digital X-ray detectors, together with advances in reconstruction algorithms, creates an opportunity for bringing 3D capabilities to conventional radiology systems. The downside is that reconstruction algorithms for non-standard acquisition protocols are generally based on iterative approaches that involve a high computational burden.The development of new flexible X-ray systems could benefit from computer simulations, which may enable performance to be checked before expensive real systems are implemented. The development of simulation/reconstruction algorithms in this context poses three main difficulties. First, the algorithms deal with large data volumes and are computationally expensive, thus leading to the need for hardware and software optimizations. Second, these optimizations are limited by the high flexibility required to explore new scanning geometries, including fully configurable positioning of source and detector elements. And third, the evolution of the various hardware setups increases the effort required for maintaining and adapting the implementations to current and future programming models. Previous works lack support for completely flexible geometries and/or compatibility with multiple programming models and platforms.In this paper, we present FUX-Sim, a novel X-ray simulation/reconstruction framework that was designed to be flexible and fast. Optimized implementation for different families of GPUs (CUDA and OpenCL) and multi-core CPUs was achieved thanks to a modularized approach based on a layered architecture and parallel implementation of the algorithms for both architectures.A detailed performance evaluation demonstrates that for different system configurations and hardware platforms, FUX-Sim maximizes performance with the CUDA programming model (5 times faster than other state-of-the-art implementations). Furthermore, the CPU and OpenCL programming models allow FUX-Sim to be executed over a wide range of hardware platforms.
Highlights
In recent decades, there has been a rapid advance towards the use of digital equipment in radiology
Optimized implementation for different families of graphic processor units (GPUs) (CUDA and OpenCL) and multi-core CPUs was achieved thanks to a modularized approach based on a layered architecture and parallel implementation of the algorithms for both architectures
More recent works have opted for graphic processor units (GPUs), with CUDA and OpenCL being the most widely used programming models [4]
Summary
There has been a rapid advance towards the use of digital equipment in radiology. Research on new configurations for X-ray systems, new acquisition protocols, and advanced reconstruction algorithms to obtain tomographic images from a limited number of projections can benefit from simulation tools, which enable evaluation of possibilities before their actual implementation in real systems. CT Sim [1] is an open source CT simulator that enables the projection of various phantoms, it is limited to 2D circular scans with ideal parallel-beam and fan-beam geometries It provides analytical reconstruction methods (FBP and Direct Fourier), without supporting iterative reconstruction algorithms. Given the high computational burden of some of the algorithms used in simulation and reconstruction, it is widely accepted that parallel implementations are needed to achieve reasonable execution times Along these lines, more recent works have opted for graphic processor units (GPUs), with CUDA and OpenCL being the most widely used programming models [4]. We detail the optimizations carried out at each layer in terms of computation and memory management and evaluate different system setups by comparing three programming models
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.